隧道突水灾害光纤光栅多元信息表征、状态辨识与预警理论研究

Water inrush disaster has became the main challenges to many fields such as traffic and hydroelectric engineering in the tunnel construction period. Real-time monitoring, state identification and early-warning of the water inrush hazards have become a key scientific problem to be urgently solved . In response to the above problems, fiber Bragg grating sensing method is regarded as the realization means of water inrush monitoring. At the same time, the academic thought that identification of the water inrush catastrophic process and early-warning of the disaster are realized by multiple characteristic information is proposed. Firstly, strain transfer mechanism of fiber Bragg grating and time-varying reconfiguration theory on load distribution are made breakthroughs. And then new method on high-precision sensing and acquisition of tunnel water disasters characterization information is established. Meanwhile, the fiber grating sensing model based on the typical water inrush disaster characterized information, such as flow velocity and strain, is going to be built. Key research will focus on the implementation method of flow velocity and direction vector sensor and 3-dimensional stress sensor. The multiple characteristic information integration intelligent sensing network is to be construct. As the key research content,numerical simulation and physical model test of tunnel water inrush are done. And multiple characteristic information response pattern and precursory features during water inrush catastrophic process are further studied. Water inrush disaster state identification and early-warning theory model would be established in tunnel. Finally, fiber grating real-time monitoring, state identification and early-warning system on water inrush are to be established combined with model test in tunnel. It has important theoretical significance and engineering value to prevention of water inrush disaster in tunnel.

突水灾害是交通、水电等领域隧道(洞)建设面临的主要挑战，突水灾害的实时监测、状态辨识和预警已成为亟待解决的关键科技难题。针对上述问题，本项目将光纤光栅传感方法作为突水灾害监测的实现方法，提出"以多元表征信息特性实现突水灾变过程综合辨识与灾害预警"的学术思路。首先，突破光纤光栅应变传递机理与荷载分布时变重构理论，建立隧道突水灾害表征信息高精度传感与获取新方法。同时，建立流速流向、应力等典型突水灾害表征信息的光纤光栅传感模型，重点研究流速流向矢量传感与植入式三维应力传感的实现方法及传感器，构建多元表征信息一体化智能传感网络。作为核心研究内容，开展隧道突水数值模拟与物理模型试验，深入研究突水灾变过程中多元表征信息响应规律与前兆特征，建立隧道突水灾害综合状态辨识与预警理论模型。最后，结合现场试验，形成隧道突水灾害光纤光栅传感实时监测、状态辨识与预警系统，研究成果对隧道突水灾害防治具有重要意义。

突水灾害已成为隧道建设所面临的巨大挑战，目前突水灾害监测与预警是一直以来备受关注而又未能很好解决的难题，其根本原因在于缺乏有效的监测传感方法和科学合理的预警辨识依据。针对上述问题,本项目主要研究了金属化封装应变传感器与植入式智能土工格栅等典型传感器的应变传递特性，有效提高l了光纤光栅传感器的精度，开发了温度/流速共采传感器、三维应力传感器、微型压力传感器、微型位移传感器与智能土工格栅等多种光纤光栅传感器，并申请了多项国家发明专利。本项目提出采用压缩感知算法实现全光谱数据的低采样采集及其重构，并基于改进自适应算法实现栅格区域非均匀应力重构，有效剔除了啁啾效应，采用改进的快速盲源分离算法实现了时变混合同波长光纤信号的复用,采用支持向量机对光纤光栅传感系统缺失数据进行修补。本项目分别以尚家湾隧道与青岛海底隧道为工程背景，采用数值模拟与地质力学模型试验相结合的方法，深入研究了隧道突涌水灾变过程中多种物理场的响应特性，成功捕捉了突水灾害前兆信息。